We develop a framework for the design of the next generation of appointment systems that dynamically learn and update patient preferences and use this information to continuously improve appointment-booking decisions. We show that by using an adaptive approach, primary-care clinics can achieve a more robust performance in terms of their revenue and the goal of meeting patients' preferences for physician and time of day.